INSPYR Solutions

Lead Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead Data Engineer, lasting 6+ months, with compensation of $70.00 - $85.00/hr. It requires strong skills in Databricks, Apache Spark, Python, SQL, and cloud platforms (AWS, Azure, GCP). A relevant degree and Databricks certification are essential.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
680
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πŸ—“οΈ - Date
November 20, 2025
πŸ•’ - Duration
More than 6 months
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🏝️ - Location
Remote
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πŸ“„ - Contract
Unknown
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πŸ”’ - Security
Unknown
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πŸ“ - Location detailed
Georgia, United States
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🧠 - Skills detailed
#AI (Artificial Intelligence) #Hugging Face #GCP (Google Cloud Platform) #Databricks #Azure Data Factory #Deployment #Scala #"ETL (Extract #Transform #Load)" #GitLab #Model Deployment #Computer Science #Leadership #Dataflow #Apache Spark #Python #S3 (Amazon Simple Storage Service) #Delta Lake #Data Lakehouse #Azure #Kafka (Apache Kafka) #Data Storage #Storage #Version Control #GitHub #Data Processing #ADF (Azure Data Factory) #Security #Data Engineering #Data Modeling #REST (Representational State Transfer) #Data Quality #SQL (Structured Query Language) #Transformers #DevOps #ADLS (Azure Data Lake Storage) #MLflow #Spark (Apache Spark) #Data Integration #Data Lake #GIT #REST API #Langchain #Azure Repos #ML (Machine Learning) #Azure DevOps #AWS Glue #Cloud #Data Pipeline #AWS (Amazon Web Services) #BI (Business Intelligence)
Role description
Title: Β Lead Data Engineer Location: Remote Duration: 6+ months Compensation: $70.00 - 85.00/hr Work Requirements: US Citizen, GC Holders or Authorized to Work in the U.S.Data Engineer Summary We are looking for a Lead Data Engineer who excels in data modeling and can build end-to-end data solutions. The ideal candidate will bring strong leadership skills, with proven experience driving projects from initiation through successful completion. Responsibilities β€’ Design, develop, and maintain scalable data pipelines using Apache Spark on Databricks. β€’ Build and manage Delta Lake architectures for efficient data storage and retrieval. β€’ Implement robust ETL/ELT workflows using Databricks notebooks, SQL, and Python. β€’ Collaborate with AI/ML teams to operationalize models within the Databricks environment. β€’ Optimize data workflows for performance, reliability, and cost-efficiency in cloud platforms (AWS, Azure, or GCP). β€’ Ensure data quality, lineage, and governance using tools like Unity Catalog and MLflow. β€’ Develop CI/CD pipelines for data and ML workflows using Databricks Repos and Git integrations. β€’ Monitor and troubleshoot production data pipelines and model deployments. Key Responsibilities β€’ Strong hands-on experience with Databricks, including Spark, Delta Lake, and MLflow. β€’ Proficiency in Python, SQL, and distributed data processing. β€’ Experience with cloud-native data services (e.g., AWS Glue, Azure Data Factory, GCP Dataflow). β€’ Familiarity with machine learning lifecycle and integration of models into data pipelines. β€’ Understanding of data warehousing, data lakehouse architecture, and real-time streaming (Kafka, Spark Structured Streaming). β€’ Experience with version control, CI/CD, and infrastructure-as-code tools. β€’ Excellent communication and collaboration skills. β€’ Certifications in Databricks (e.g., Databricks Certified Data Engineer Associate/Professional). β€’ Experience with feature engineering and feature stores in Databricks. β€’ Exposure to MLOps practices and tools. β€’ Bachelor's or Master's degree in Computer Science, Data Engineering, or related field. β€’ Leveraged Databricks for scalable AI and BI solutions, integrating well-known large language models (Anthropic, LLaMA, Gemini) to enhance data-driven insights. Developed agentic AI agents to automate complex decision-making workflows. Technology Stack β€’ Databricks (Spark, Delta Lake, MLflow, Notebooks) β€’ Python & SQL β€’ Apache Spark (via Databricks) β€’ Delta Lake (for lakehouse architecture) β€’ Cloud Platforms β€’ Azure, AWS, or GCP β€’ Cloud Storage (ADLS, S3, GCS) β€’ Data Integration β€’ Kafka or Event Hubs (streaming) β€’ Auto Loader (Databricks file ingestion) β€’ REST APIs β€’ AI/ML β€’ MLflow (model tracking/deployment) β€’ Hugging Face Transformers β€’ LangChain / LlamaIndex (LLM integration) β€’ LLMs: Anthropic Claude, Meta LLaMA, Google Gemini β€’ DevOps β€’ Git (GitHub, GitLab, Azure Repos) β€’ Databricks Repos β€’ CI/CD: GitHub Actions, Azure DevOps β€’ Security & Governance β€’ Unity Catalog β€’ RBAC Our benefits package includes: β€’ Comprehensive medical benefits β€’ Competitive pay β€’ 401(k) retirement plan β€’ ...and much more! About INSPYR Solutions Technology is our focus and quality is our commitment. As a national expert in delivering flexible technology and talent solutions, we strategically align industry and technical expertise with our clients' business objectives and cultural needs. Our solutions are tailored to each client and include a wide variety of professional services, project, and talent solutions. By always striving for excellence and focusing on the human aspect of our business, we work seamlessly with our talent and clients to match the right solutions to the right opportunities. Learn more about us at inspyrsolutions.com. INSPYR Solutions provides Equal Employment Opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. In addition to federal law requirements, INSPYR Solutions complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. #IND-TELECOM Information collected and processed through your application with INSPYR Solutions (including any job applications you choose to submit) is subject to INSPYR Solutions’ Privacy Policy and INSPYR Solutions’ AI and Automated Employment Decision Tool Policy: https://www.inspyrsolutions.com/policies/. By submitting an application, you are consenting to being contacted by INSPYR Solutions through phone, email, or text.